Relative Abundance in Samples at Different Taxonomic Ranks
2. Order
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -8.7
Scaled residuals:
Min 1Q Median 3Q Max
-1.88064 -0.79685 -0.02963 0.59519 1.89864
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 0.001563 0.03953
Residual 0.031106 0.17637
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.78132 0.06832 21.60557 11.436 1.24e-10 ***
DietPEITC -0.01420 0.06167 15.00000 -0.230 0.8210
Week9 -0.13800 0.05879 17.00000 -2.347 0.0313 *
SexMale -0.01632 0.06541 15.00000 -0.250 0.8064
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.451
Week9 -0.430 0.000
SexMale -0.638 0.000 0.000
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -66.7
Scaled residuals:
Min 1Q Median 3Q Max
-1.7791 -0.4749 -0.1250 0.5636 1.5018
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 0.001600 0.04000
Residual 0.004052 0.06366
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.301785 0.030304 19.154067 9.959 5.2e-09 ***
DietPEITC 0.040279 0.028386 15.000000 1.419 0.176
Week9 0.007554 0.021219 17.000000 0.356 0.726
SexMale -0.020233 0.030107 15.000000 -0.672 0.512
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.468
Week9 -0.350 0.000
SexMale -0.662 0.000 0.000
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -72.5
Scaled residuals:
Min 1Q Median 3Q Max
-1.5175 -0.5912 -0.1733 0.3819 2.5513
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 0.001321 0.03635
Residual 0.003380 0.05814
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.102089 0.027624 19.171460 3.696 0.00152 **
DietPEITC -0.003192 0.025869 15.000000 -0.123 0.90344
Week9 0.014756 0.019379 17.000000 0.761 0.45685
SexMale -0.019666 0.027438 15.000000 -0.717 0.48455
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.468
Week9 -0.351 0.000
SexMale -0.662 0.000 0.000
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -77.9
Scaled residuals:
Min 1Q Median 3Q Max
-1.1103 -0.6064 -0.2816 0.1003 3.0040
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 0.000000 0.0000
Residual 0.003745 0.0612
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.02051 0.02281 32.00000 0.899 0.375
DietPEITC -0.02449 0.02040 32.00000 -1.200 0.239
Week9 0.02749 0.02040 32.00000 1.348 0.187
SexMale 0.02169 0.02164 32.00000 1.002 0.324
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.447
Week9 -0.447 0.000
SexMale -0.632 0.000 0.000
convergence code: 0
singular fit
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -154.4
Scaled residuals:
Min 1Q Median 3Q Max
-1.7893 -0.5766 -0.1732 0.5219 2.6925
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 0.0000000 0.00000
Residual 0.0003437 0.01854
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.023133 0.006909 32.000000 3.348 0.00209 **
DietPEITC -0.001633 0.006180 32.000000 -0.264 0.79330
Week9 -0.004655 0.006180 32.000000 -0.753 0.45679
SexMale 0.013373 0.006555 32.000000 2.040 0.04964 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.447
Week9 -0.447 0.000
SexMale -0.632 0.000 0.000
convergence code: 0
singular fit
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -165
Scaled residuals:
Min 1Q Median 3Q Max
-1.3061 -0.6061 -0.2231 0.2306 2.6532
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 1.815e-05 0.00426
Residual 2.299e-04 0.01516
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.025010 0.005997 21.300677 4.170 0.000422 ***
DietPEITC -0.004875 0.005439 15.000000 -0.896 0.384234
Week9 0.010158 0.005055 17.000000 2.010 0.060605 .
SexMale -0.012252 0.005769 15.000000 -2.124 0.050726 .
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.453
Week9 -0.421 0.000
SexMale -0.641 0.000 0.000
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -193.2
Scaled residuals:
Min 1Q Median 3Q Max
-2.0282 -0.5465 -0.2278 0.3549 2.5848
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 0.0000000 0.00000
Residual 0.0001022 0.01011
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.015935 0.003768 32.000000 4.229 0.000183 ***
DietPEITC 0.002352 0.003370 32.000000 0.698 0.490287
Week9 0.006505 0.003370 32.000000 1.930 0.062526 .
SexMale -0.002283 0.003575 32.000000 -0.639 0.527587
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.447
Week9 -0.447 0.000
SexMale -0.632 0.000 0.000
convergence code: 0
singular fit
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -210.5
Scaled residuals:
Min 1Q Median 3Q Max
-1.5819 -0.5291 -0.0690 0.4427 2.0626
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 1.333e-05 0.003651
Residual 4.833e-05 0.006952
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.0125649 0.0031105 19.7698410 4.039 0.000654 ***
DietPEITC -0.0029065 0.0028867 15.0000000 -1.007 0.329968
Week9 0.0130555 0.0023173 17.0000000 5.634 2.98e-05 ***
SexMale 0.0001131 0.0030618 15.0000000 0.037 0.971031
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.464
Week9 -0.372 0.000
SexMale -0.656 0.000 0.000
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -172.5
Scaled residuals:
Min 1Q Median 3Q Max
-1.2638 -0.4796 -0.1511 0.1920 2.1671
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 0.0001244 0.01115
Residual 0.0001132 0.01064
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.005056 0.006585 17.342670 0.768 0.453
DietPEITC 0.001276 0.006342 15.000000 0.201 0.843
Week9 -0.002087 0.003546 17.000000 -0.589 0.564
SexMale 0.010681 0.006726 15.000000 1.588 0.133
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.482
Week9 -0.269 0.000
SexMale -0.681 0.000 0.000
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -212.7
Scaled residuals:
Min 1Q Median 3Q Max
-1.2122 -0.6591 -0.0984 0.1636 3.3008
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 0.000e+00 0.000000
Residual 5.542e-05 0.007444
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 5.246e-03 2.774e-03 3.200e+01 1.891 0.06771 .
DietPEITC 2.357e-03 2.481e-03 3.200e+01 0.950 0.34931
Week9 -9.545e-05 2.481e-03 3.200e+01 -0.038 0.96955
SexMale 7.225e-03 2.632e-03 3.200e+01 2.745 0.00984 **
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.447
Week9 -0.447 0.000
SexMale -0.632 0.000 0.000
convergence code: 0
singular fit
3. Family
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -88.1
Scaled residuals:
Min 1Q Median 3Q Max
-1.60111 -0.71235 -0.09878 0.68056 2.05345
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 0.0001745 0.01321
Residual 0.0025703 0.05070
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.1770761 0.0198937 21.4147747 8.901 1.21e-08 ***
DietPEITC -0.0061098 0.0180100 15.0000000 -0.339 0.739
Week9 -0.0005112 0.0168994 17.0000000 -0.030 0.976
SexMale 0.0057442 0.0191025 15.0000000 0.301 0.768
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.453
Week9 -0.425 0.000
SexMale -0.640 0.000 0.000
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -105.8
Scaled residuals:
Min 1Q Median 3Q Max
-1.5931 -0.4595 -0.1037 0.7204 1.6591
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 0.0003528 0.01878
Residual 0.0012728 0.03568
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.153096 0.015974 19.761954 9.584 7.2e-09 ***
DietPEITC 0.018033 0.014826 15.000000 1.216 0.243
Week9 -0.009526 0.011892 17.000000 -0.801 0.434
SexMale 0.013876 0.015726 15.000000 0.882 0.392
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.464
Week9 -0.372 0.000
SexMale -0.656 0.000 0.000
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -107.4
Scaled residuals:
Min 1Q Median 3Q Max
-1.63580 -0.53632 0.06688 0.52915 1.80130
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 0.0003399 0.01844
Residual 0.0012101 0.03479
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.15149 0.01561 19.74051 9.706 5.9e-09 ***
DietPEITC 0.00297 0.01449 15.00000 0.205 0.8404
Week9 0.01396 0.01160 17.00000 1.204 0.2452
SexMale -0.03442 0.01537 15.00000 -2.240 0.0407 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.464
Week9 -0.371 0.000
SexMale -0.657 0.000 0.000
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -98.8
Scaled residuals:
Min 1Q Median 3Q Max
-1.8606 -0.5603 -0.0763 0.3475 3.5612
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 1.071e-20 1.035e-10
Residual 1.950e-03 4.416e-02
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.108746 0.016457 32.000000 6.608 1.89e-07 ***
DietPEITC 0.001277 0.014720 32.000000 0.087 0.93139
Week9 -0.042848 0.014720 32.000000 -2.911 0.00651 **
SexMale 0.027205 0.015613 32.000000 1.742 0.09103 .
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.447
Week9 -0.447 0.000
SexMale -0.632 0.000 0.000
convergence code: 0
singular fit
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -141.8
Scaled residuals:
Min 1Q Median 3Q Max
-2.0688 -0.3466 -0.1241 0.4407 1.7068
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 0.0001305 0.01142
Residual 0.0004022 0.02006
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.090440 0.009212 19.498049 9.818 5.51e-09 ***
DietPEITC 0.013562 0.008584 15.000000 1.580 0.1350
Week9 0.012558 0.006685 17.000000 1.878 0.0776 .
SexMale -0.011137 0.009105 15.000000 -1.223 0.2401
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.466
Week9 -0.363 0.000
SexMale -0.659 0.000 0.000
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -72.1
Scaled residuals:
Min 1Q Median 3Q Max
-1.5145 -0.5913 -0.1708 0.3789 2.5421
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 0.001334 0.03653
Residual 0.003426 0.05853
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.102613 0.027792 19.177997 3.692 0.00153 **
DietPEITC -0.003133 0.026023 15.000000 -0.120 0.90578
Week9 0.015114 0.019511 17.000000 0.775 0.44920
SexMale -0.019653 0.027602 15.000000 -0.712 0.48739
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.468
Week9 -0.351 0.000
SexMale -0.662 0.000 0.000
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -99.9
Scaled residuals:
Min 1Q Median 3Q Max
-1.5166 -0.5669 -0.1138 0.3653 2.1566
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 0.0004683 0.02164
Residual 0.0015036 0.03878
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.100219 0.017689 19.567623 5.666 1.65e-05 ***
DietPEITC -0.008283 0.016466 15.000000 -0.503 0.6223
Week9 -0.034696 0.012925 17.000000 -2.684 0.0157 *
SexMale -0.015533 0.017465 15.000000 -0.889 0.3878
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.465
Week9 -0.365 0.000
SexMale -0.658 0.000 0.000
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -157.4
Scaled residuals:
Min 1Q Median 3Q Max
-1.8108 -0.5849 -0.0726 0.3764 3.5513
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 3.658e-21 6.048e-11
Residual 3.123e-04 1.767e-02
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.038395 0.006586 32.000000 5.830 1.78e-06 ***
DietPEITC 0.005802 0.005890 32.000000 0.985 0.332
Week9 -0.009270 0.005890 32.000000 -1.574 0.125
SexMale 0.009273 0.006248 32.000000 1.484 0.148
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.447
Week9 -0.447 0.000
SexMale -0.632 0.000 0.000
convergence code: 0
singular fit
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -77.5
Scaled residuals:
Min 1Q Median 3Q Max
-1.1125 -0.6068 -0.2800 0.1023 3.0168
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 0.000000 0.00000
Residual 0.003799 0.06164
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.02060 0.02297 32.00000 0.897 0.376
DietPEITC -0.02473 0.02055 32.00000 -1.204 0.237
Week9 0.02784 0.02055 32.00000 1.355 0.185
SexMale 0.02187 0.02179 32.00000 1.004 0.323
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.447
Week9 -0.447 0.000
SexMale -0.632 0.000 0.000
convergence code: 0
singular fit
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -164.6
Scaled residuals:
Min 1Q Median 3Q Max
-1.3062 -0.6051 -0.2223 0.2252 2.6604
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 1.841e-05 0.00429
Residual 2.327e-04 0.01525
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.025158 0.006034 21.298658 4.170 0.000422 ***
DietPEITC -0.004893 0.005472 15.000000 -0.894 0.385299
Week9 0.010263 0.005084 17.000000 2.018 0.059612 .
SexMale -0.012328 0.005804 15.000000 -2.124 0.050703 .
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.453
Week9 -0.421 0.000
SexMale -0.641 0.000 0.000
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -192.7
Scaled residuals:
Min 1Q Median 3Q Max
-2.0323 -0.5466 -0.2314 0.3530 2.5993
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 1.499e-24 1.224e-12
Residual 1.036e-04 1.018e-02
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.016024 0.003793 32.000000 4.224 0.000186 ***
DietPEITC 0.002365 0.003393 32.000000 0.697 0.490745
Week9 0.006599 0.003393 32.000000 1.945 0.060594 .
SexMale -0.002279 0.003599 32.000000 -0.633 0.530979
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.447
Week9 -0.447 0.000
SexMale -0.632 0.000 0.000
convergence code: 0
singular fit
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -209.8
Scaled residuals:
Min 1Q Median 3Q Max
-1.58406 -0.51959 -0.06268 0.44086 2.05003
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 1.389e-05 0.003727
Residual 4.934e-05 0.007024
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.012621 0.003153 19.736868 4.003 0.000713 ***
DietPEITC -0.002916 0.002927 15.000000 -0.996 0.334880
Week9 0.013219 0.002341 17.000000 5.646 2.91e-05 ***
SexMale 0.000146 0.003105 15.000000 0.047 0.963114
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.464
Week9 -0.371 0.000
SexMale -0.657 0.000 0.000
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -164.2
Scaled residuals:
Min 1Q Median 3Q Max
-1.25768 -0.54967 -0.15591 0.03543 2.93539
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 0.0000000 0.00000
Residual 0.0002525 0.01589
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.016173 0.005922 32.000000 2.731 0.0102 *
DietPEITC -0.004024 0.005297 32.000000 -0.760 0.4530
Week9 -0.002386 -0.450 0.6555
SexMale 0.005075 0.005619 32.000000 0.903 0.3731
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.447
Week9 -0.447 0.000
SexMale -0.632 0.000 0.000
convergence code: 0
singular fit
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -234.6
Scaled residuals:
Min 1Q Median 3Q Max
-1.75217 -0.66162 -0.05052 0.46837 2.28674
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 9.420e-07 0.0009706
Residual 2.712e-05 0.0052074
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.015682 0.001994 21.782186 7.865 8.38e-08 ***
DietPEITC 0.001572 0.001795 15.000000 0.876 0.3950
Week9 0.001316 0.001736 17.000000 0.758 0.4589
SexMale -0.004338 0.001904 15.000000 -2.278 0.0378 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.450
Week9 -0.435 0.000
SexMale -0.637 0.000 0.000
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -211.9
Scaled residuals:
Min 1Q Median 3Q Max
-1.71477 -0.74456 -0.07438 0.39424 2.95175
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 0.000e+00 0.000000
Residual 5.684e-05 0.007539
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.006852 0.002810 32.000000 2.439 0.02047 *
DietPEITC 0.002478 0.002513 32.000000 0.986 0.33150
Week9 -0.002141 0.002513 32.000000 -0.852 0.40052
SexMale 0.008180 0.002666 32.000000 3.069 0.00436 **
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.447
Week9 -0.447 0.000
SexMale -0.632 0.000 0.000
convergence code: 0
singular fit
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -172
Scaled residuals:
Min 1Q Median 3Q Max
-1.2612 -0.4798 -0.1519 0.1907 2.1592
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 0.0001261 0.01123
Residual 0.0001148 0.01071
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.005083 0.006631 17.343439 0.767 0.454
DietPEITC 0.001258 0.006386 15.000000 0.197 0.846
Week9 -0.002073 0.003571 17.000000 -0.581 0.569
SexMale 0.010777 0.006773 15.000000 1.591 0.132
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.482
Week9 -0.269 0.000
SexMale -0.681 0.000 0.000
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -212.3
Scaled residuals:
Min 1Q Median 3Q Max
-1.2131 -0.6659 -0.0985 0.1594 3.2848
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 0.000e+00 0.000000
Residual 5.619e-05 0.007496
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 5.251e-03 2.794e-03 3.200e+01 1.879 0.06932 .
DietPEITC 2.400e-03 2.499e-03 3.200e+01 0.960 0.34402
Week9 -5.995e-05 2.499e-03 3.200e+01 -0.024 0.98101
SexMale 7.284e-03 2.650e-03 3.200e+01 2.748 0.00976 **
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.447
Week9 -0.447 0.000
SexMale -0.632 0.000 0.000
convergence code: 0
singular fit
4. Genus
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -78
Scaled residuals:
Min 1Q Median 3Q Max
-1.63210 -0.56445 0.04123 0.48143 1.80125
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 0.0007937 0.02817
Residual 0.0030741 0.05544
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.221816 0.024563 19.877004 9.031 1.8e-08 ***
DietPEITC 0.007364 0.022758 15.000000 0.324 0.7507
Week9 0.017904 0.018482 17.000000 0.969 0.3462
SexMale -0.055533 0.024139 15.000000 -2.301 0.0362 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.463
Week9 -0.376 0.000
SexMale -0.655 0.000 0.000
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -46.6
Scaled residuals:
Min 1Q Median 3Q Max
-1.3819 -0.5776 -0.1677 0.4200 2.9199
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 0.001923 0.04385
Residual 0.008340 0.09132
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.151399 0.039821 20.053857 3.802 0.00111 **
DietPEITC -0.008327 0.036797 15.000000 -0.226 0.82403
Week9 0.021242 0.030441 17.000000 0.698 0.49473
SexMale -0.033004 0.039029 15.000000 -0.846 0.41104
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.462
Week9 -0.382 0.000
SexMale -0.653 0.000 0.000
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -76.2
Scaled residuals:
Min 1Q Median 3Q Max
-1.5239 -0.5267 -0.1182 0.3308 2.0518
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 0.0009331 0.03055
Residual 0.0031798 0.05639
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.14406 0.02548 19.66782 5.655 1.66e-05 ***
DietPEITC -0.01101 0.02368 15.00000 -0.465 0.6487
Week9 -0.05339 0.01880 17.00000 -2.841 0.0113 *
SexMale -0.02325 0.02511 15.00000 -0.926 0.3693
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.465
Week9 -0.369 0.000
SexMale -0.657 0.000 0.000
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -115.6
Scaled residuals:
Min 1Q Median 3Q Max
-1.34918 -0.73243 -0.00275 0.53784 2.36896
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 0.000000 0.00000
Residual 0.001154 0.03397
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.112485 0.012659 32.000000 8.886 3.76e-10 ***
DietPEITC -0.007202 0.011322 32.000000 -0.636 0.52926
Week9 -0.036697 0.011322 32.000000 -3.241 0.00278 **
SexMale 0.003498 0.012009 32.000000 0.291 0.77275
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.447
Week9 -0.447 0.000
SexMale -0.632 0.000 0.000
convergence code: 0
singular fit
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -57.1
Scaled residuals:
Min 1Q Median 3Q Max
-1.10205 -0.60242 -0.29339 0.09924 2.98219
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 0.000000 0.00000
Residual 0.007171 0.08468
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.02774 0.03156 32.00000 0.879 0.386
DietPEITC -0.03294 0.02823 32.00000 -1.167 0.252
Week9 0.03759 0.02823 32.00000 1.332 0.192
SexMale 0.03065 0.02994 32.00000 1.024 0.314
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.447
Week9 -0.447 0.000
SexMale -0.632 0.000 0.000
convergence code: 0
singular fit
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -140.8
Scaled residuals:
Min 1Q Median 3Q Max
-2.0366 -0.5651 -0.0398 0.4775 3.3796
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 0.0000000 0.00000
Residual 0.0005249 0.02291
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.038158 0.008539 32.000000 4.469 9.23e-05 ***
DietPEITC 0.002742 0.007637 32.000000 0.359 0.7219
Week9 -0.010344 0.007637 32.000000 -1.354 0.1851
SexMale 0.017576 0.008100 32.000000 2.170 0.0376 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.447
Week9 -0.447 0.000
SexMale -0.632 0.000 0.000
convergence code: 0
singular fit
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -138.2
Scaled residuals:
Min 1Q Median 3Q Max
-1.6003 -0.4125 -0.0523 0.2003 4.2777
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 6.136e-05 0.007833
Residual 5.148e-04 0.022690
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.031908 0.009227 20.915532 3.458 0.00236 **
DietPEITC 0.005791 0.008417 15.000000 0.688 0.50193
Week9 -0.015938 0.007563 17.000000 -2.107 0.05024 .
SexMale 0.016989 0.008927 15.000000 1.903 0.07640 .
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.456
Week9 -0.410 0.000
SexMale -0.645 0.000 0.000
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -163.8
Scaled residuals:
Min 1Q Median 3Q Max
-1.4281 -0.7365 -0.1075 0.6820 2.8405
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 0.0000000 0.00000
Residual 0.0002556 0.01599
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.028421 0.005959 32.000000 4.770 3.88e-05 ***
DietPEITC -0.001827 0.005329 32.000000 -0.343 0.734
Week9 -0.003393 0.005329 32.000000 -0.637 0.529
SexMale 0.008109 0.005653 32.000000 1.434 0.161
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.447
Week9 -0.447 0.000
SexMale -0.632 0.000 0.000
convergence code: 0
singular fit
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -140.9
Scaled residuals:
Min 1Q Median 3Q Max
-1.52933 -0.44239 -0.09445 0.34429 2.61033
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 0.0003370 0.01836
Residual 0.0003017 0.01737
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.001755 0.010806 17.317633 0.162 0.8729
DietPEITC 0.009001 0.010412 15.000000 0.865 0.4009
Week9 0.012822 0.005790 17.000000 2.215 0.0407 *
SexMale 0.020592 0.011043 15.000000 1.865 0.0819 .
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.482
Week9 -0.268 0.000
SexMale -0.681 0.000 0.000
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -206.7
Scaled residuals:
Min 1Q Median 3Q Max
-1.66463 -0.45658 -0.00022 0.57123 1.44058
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 3.564e-05 0.005970
Residual 4.202e-05 0.006482
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.0264022 0.0037090 17.7755540 7.118 1.33e-06 ***
DietPEITC 0.0004637 0.0035482 15.0000000 0.131 0.898
Week9 0.0005568 0.0021608 17.0000000 0.258 0.800
SexMale -0.0025087 0.0037634 15.0000000 -0.667 0.515
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.478
Week9 -0.291 0.000
SexMale -0.676 0.000 0.000
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -189.4
Scaled residuals:
Min 1Q Median 3Q Max
-1.48980 -0.57990 -0.03277 0.61880 2.37731
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 1.945e-05 0.004410
Residual 9.826e-05 0.009913
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.0178184 0.0042391 20.2799064 4.203 0.000426 ***
DietPEITC -0.0038745 0.0039039 15.0000000 -0.992 0.336707
Week9 0.0178741 0.0033042 17.0000000 5.410 4.7e-05 ***
SexMale -0.0001652 0.0041407 15.0000000 -0.040 0.968710
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.460
Week9 -0.390 0.000
SexMale -0.651 0.000 0.000
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -216.5
Scaled residuals:
Min 1Q Median 3Q Max
-1.97448 -0.46880 0.00346 0.41374 1.95257
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 2.163e-05 0.004651
Residual 3.334e-05 0.005774
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.021520 0.003072 18.250697 7.005 1.42e-06 ***
DietPEITC 0.009019 0.002918 15.000000 3.091 0.00745 **
Week9 0.001835 0.001925 17.000000 0.954 0.35364
SexMale -0.006249 0.003094 15.000000 -2.019 0.06168 .
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.475
Week9 -0.313 0.000
SexMale -0.672 0.000 0.000
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -145.4
Scaled residuals:
Min 1Q Median 3Q Max
-1.29599 -0.55010 -0.17246 0.08279 2.99174
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 0.0000000 0.00000
Residual 0.0004548 0.02133
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.022358 0.007947 32.000000 2.813 0.00832 **
DietPEITC -0.005786 0.007108 32.000000 -0.814 0.42170
Week9 -0.003311 0.007108 32.000000 -0.466 0.64449
SexMale 0.006961 0.007540 32.000000 0.923 0.36282
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.447
Week9 -0.447 0.000
SexMale -0.632 0.000 0.000
convergence code: 0
singular fit
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -150.4
Scaled residuals:
Min 1Q Median 3Q Max
-1.5515 -0.5585 -0.2031 0.2320 3.2075
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 4.318e-05 0.006571
Residual 3.508e-04 0.018729
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.037005 0.007636 20.880617 4.846 8.76e-05 ***
DietPEITC -0.009206 0.006969 15.000000 -1.321 0.2063
Week9 0.004484 0.006243 16.999999 0.718 0.4823
SexMale -0.020180 0.007392 15.000000 -2.730 0.0155 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.456
Week9 -0.409 0.000
SexMale -0.645 0.000 0.000
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -207.1
Scaled residuals:
Min 1Q Median 3Q Max
-1.6546 -0.3912 -0.1061 0.2386 2.6179
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 3.400e-05 0.005831
Residual 4.219e-05 0.006496
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.0143734 0.0036627 17.8647574 3.924 0.00101 **
DietPEITC 0.0055563 0.0034991 15.0000000 1.588 0.13315
Week9 -0.0007885 0.0021652 17.0000000 -0.364 0.72022
SexMale 0.0028537 0.0037113 15.0000000 0.769 0.45388
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.478
Week9 -0.296 0.000
SexMale -0.676 0.000 0.000
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -154.4
Scaled residuals:
Min 1Q Median 3Q Max
-1.3726 -0.4899 -0.1808 0.2291 1.9940
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 0.0002100 0.01449
Residual 0.0002027 0.01424
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.0074028 0.0086494 17.4388218 0.856 0.404
DietPEITC 0.0009598 0.0083176 15.0000000 0.115 0.910
Week9 -0.0025600 0.0047455 17.0000000 -0.539 0.597
SexMale 0.0142217 0.0088221 15.0000000 1.612 0.128
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.481
Week9 -0.274 0.000
SexMale -0.680 0.000 0.000
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -227.7
Scaled residuals:
Min 1Q Median 3Q Max
-1.6473 -0.6063 -0.0781 0.4457 2.6780
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 1.034e-05 0.003216
Residual 2.647e-05 0.005145
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.012992 0.002444 19.172144 5.316 3.83e-05 ***
DietPEITC 0.002198 0.002289 15.000000 0.961 0.352
Week9 -0.001209 0.001715 17.000000 -0.705 0.490
SexMale 0.002587 0.002428 15.000000 1.066 0.303
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.468
Week9 -0.351 0.000
SexMale -0.662 0.000 0.000
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -189
Scaled residuals:
Min 1Q Median 3Q Max
-1.4055 -0.5709 -0.2243 0.3268 2.5765
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 0.0000000 0.00000
Residual 0.0001163 0.01079
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.013853 0.004020 32.000000 3.446 0.00161 **
DietPEITC 0.003843 0.003595 32.000000 1.069 0.29312
Week9 0.001858 0.003595 32.000000 0.517 0.60888
SexMale -0.002346 0.003814 32.000000 -0.615 0.54279
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.447
Week9 -0.447 0.000
SexMale -0.632 0.000 0.000
convergence code: 0
singular fit
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -195.6
Scaled residuals:
Min 1Q Median 3Q Max
-1.5832 -0.6877 -0.1004 0.3424 3.1606
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 0.000e+00 0.000000
Residual 9.459e-05 0.009726
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.008395 0.003625 32.000000 2.316 0.02711 *
DietPEITC 0.002268 0.003242 32.000000 0.700 0.48919
Week9 -0.002141 0.003242 32.000000 -0.660 0.51374
SexMale 0.009805 0.003439 32.000000 2.852 0.00756 **
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.447
Week9 -0.447 0.000
SexMale -0.632 0.000 0.000
convergence code: 0
singular fit
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: lgt ~ Diet + Week + Sex + (1 | MouseID)
Data: tmp
REML criterion at convergence: -195.2
Scaled residuals:
Min 1Q Median 3Q Max
-1.0324 -0.7033 -0.1194 0.2529 3.4519
Random effects:
Groups Name Variance Std.Dev.
MouseID (Intercept) 0.000e+00 0.00000
Residual 9.585e-05 0.00979
Number of obs: 36, groups: MouseID, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 5.517e-03 3.649e-03 3.200e+01 1.512 0.1403
DietPEITC 3.543e-03 3.263e-03 3.200e+01 1.086 0.2857
Week9 6.316e-05 3.263e-03 3.200e+01 0.019 0.9847
SexMale 8.923e-03 3.461e-03 3.200e+01 2.578 0.0148 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) DPEITC Week9
DietPEITC -0.447
Week9 -0.447 0.000
SexMale -0.632 0.000 0.000
convergence code: 0
singular fit
---
title: "Nrf2 BL6 PEITC 16S Microbiome Logit-Transformed Data Modeling"
output:
  html_notebook: default
  html_document:
    df_print: paged
  pdf_document: default
---


```{r Data, warning=FALSE,echo=FALSE,message=FALSE}
# html_notebook: default

require(data.table)
require(phyloseq)
require(ggplot2)
require(plotly)
require(DT)
require(lmerTest)
source("source/functions_v2.R")

# Load data----
# Counts
load("data/ps.RData")

# Taxonomy
load("data/taxa.plus.RData")
taxa <- data.table(seq16s = rownames(taxa.plus),
                   taxa.plus)

# Samples
# ps@sam_data
load("data/samples.RData")
samples$Sample <- substr(x = samples$Name,
                         start = 1,
                         stop = 5)
samples$Sample[samples$Sample %in% c("4A_S1",
                                     "4B_S2",
                                     "4C_S3")] <- 
  substr(x = samples$Sample[samples$Sample %in% c("4A_S1",
                                                  "4B_S2",
                                                  "4C_S3")],
         start = 1,
         stop = 2)
samples$MouseID <- substr(x = samples$Sample,
                         start = 2,
                         stop = 5)
# DT::datatable(samples)
```

## Relative Abundance in Samples at Different Taxonomic Ranks
```{r Tax, warning=FALSE,echo=FALSE,message=FALSE}
# keep controls and PEITCs at weeks 5 and 9 only
w59 <- prune_samples(samples = sample_names(ps)[!(sample_names(ps) %in%
                                                    c("4A",
                                                      "4B",
                                                      "4C",
                                                      "Undetermined"))],
                    x = ps)
# OTU table
otu <- t(w59@otu_table@.Data)
otu <- data.table(seq16s = rownames(otu),
                  otu)

# Merge taxonomy and counts tables----
dt1 <- merge(taxa,
             otu,
             by = "seq16s")
dt1$seq16s <- NULL

# Remove archea and eucaryota----
dt1 <- droplevels(dt1[Kingdom == "Bacteria", ])
# 10,197 out of 10,759 rows left

# Remove rows with all zeros----
ndx.keep <- rowSums(dt1[, `5A1-C`:`9C3-P`]) > 0
dt1 <- dt1[ndx.keep, ]
# 9,877 rows left
```

### 1. Class
```{r Class, warning=FALSE,echo=FALSE,message=FALSE,fig.width=10,fig.height=7}
tax <- "Class"
dt2 <- counts_ra_by_tax_rank(dt1, tax)

mu <- aggregate(dt2$RA,
                by = list(Tax = dt2$Tax,
                          Week = dt2$Week,
                          Diet = dt2$Diet),
                FUN = "mean")

lvls <- aggregate(dt2$RA,
                  by = list(Tax = dt2$Tax),
                  FUN = "mean")
lvls <- lvls$Tax[order(lvls$x,
                       decreasing = TRUE)]

dt2$Tax <- factor(dt2$Tax,
                  levels = lvls)

dt2 <- droplevels(dt2)
dt2[, lgt := log(1 + (RA/(1-RA)))]
# length(unique(dt2$Tax))
# 26 unique classes

dt2$Group <- paste("Week",
                   dt2$Week,
                   dt2$Diet)
# unique(dt2$grp)
dt2$Group <- factor(dt2$Group,
                    levels = c("Week 5 AIN93M Control",
                               "Week 9 AIN93M Control",
                               "Week 5 PEITC",
                               "Week 9 PEITC"))

# Boxplots for Classes with RA ~>1% (minus ----
over1pct <- levels(dt2$Tax)[1:7]

for (i in 1:length(over1pct)) {
  tmp <- droplevels(dt2[Tax == over1pct[i], ])
  
  p1 <- ggplot(data = tmp) +
    facet_wrap(~ Sex,
               nrow = 1) +
    geom_line(aes(x = Group,
                  y = RA,
                  group = MouseID),
              size = 1,
              position = position_dodge(0.3)) + 
    geom_point(aes(x = Group,
                   y = RA,
                   fill = MouseID),
               size = 3,
               alpha = 0.6,
               shape = 21,
               position = position_dodge(0.3)) + 
    scale_x_discrete("Diet/Week") + 
    scale_y_continuous("Relative Abundance") + 
    scale_fill_discrete("Mouse ID") +
    ggtitle(paste(tax,
                  over1pct[i],
                  sep = ": ")) +
    theme(plot.title = element_text(hjust = 0.5),
          axis.text.x = element_text(angle = 45,
                                     hjust = 1))
  print(ggplotly(p1))
  
  p2 <- ggplot(data = tmp) +
    facet_wrap(~ Sex,
               nrow = 1) +
    geom_line(aes(x = Group,
                  y = lgt,
                  group = MouseID),
              size = 1,
              position = position_dodge(0.3)) + 
    geom_point(aes(x = Group,
                   y = lgt,
                   fill = MouseID),
               size = 3,
               alpha = 0.6,
               shape = 21,
               position = position_dodge(0.3)) + 
    scale_x_discrete("Diet/Week") + 
    scale_y_continuous("Logit of Relative Abundance") + 
    scale_fill_discrete("Mouse ID") +
    ggtitle(paste(tax,
                  over1pct[i],
                  sep = ": ")) +
    theme(plot.title = element_text(hjust = 0.5),
          axis.text.x = element_text(angle = 45,
                                     hjust = 1))
  print(ggplotly(p2))
  
  m1 <- lmerTest::lmer(lgt ~ Diet + Week + Sex + (1|MouseID),
                       # weights = 1/(Counts + 0.5),
                       data = tmp)
  print(summary(m1))
}
```

### 2. Order
```{r Order, warning=FALSE,echo=FALSE,message=FALSE,fig.width=10,fig.height=7}
tax <- "Order"
dt2 <- counts_ra_by_tax_rank(dt1, tax)

mu <- aggregate(dt2$RA,
                by = list(Tax = dt2$Tax,
                          Week = dt2$Week,
                          Diet = dt2$Diet),
                FUN = "mean")

lvls <- aggregate(dt2$RA,
                  by = list(Tax = dt2$Tax),
                  FUN = "mean")
lvls <- lvls$Tax[order(lvls$x,
                       decreasing = TRUE)]

dt2$Tax <- factor(dt2$Tax,
                  levels = lvls)

dt2 <- droplevels(dt2)
dt2[, lgt := log(1 + (RA/(1-RA)))]
# length(unique(dt2$Tax))
# 26 unique classes

dt2$Group <- paste("Week",
                   dt2$Week,
                   dt2$Diet)
# unique(dt2$grp)
dt2$Group <- factor(dt2$Group,
                    levels = c("Week 5 AIN93M Control",
                               "Week 9 AIN93M Control",
                               "Week 5 PEITC",
                               "Week 9 PEITC"))

# Boxplots for Classes with RA ~>1% (minus ----
over1pct <- levels(dt2$Tax)[1:10]

for (i in 1:length(over1pct)) {
  tmp <- droplevels(dt2[Tax == over1pct[i], ])
  
  p1 <- ggplot(data = tmp) +
    facet_wrap(~ Sex,
               nrow = 1) +
    geom_line(aes(x = Group,
                  y = RA,
                  group = MouseID),
              size = 1,
              position = position_dodge(0.3)) + 
    geom_point(aes(x = Group,
                   y = RA,
                   fill = MouseID),
               size = 3,
               alpha = 0.6,
               shape = 21,
               position = position_dodge(0.3)) + 
    scale_x_discrete("Diet/Week") + 
    scale_y_continuous("Relative Abundance") + 
    scale_fill_discrete("Mouse ID") +
    ggtitle(paste(tax,
                  over1pct[i],
                  sep = ": ")) +
    theme(plot.title = element_text(hjust = 0.5),
          axis.text.x = element_text(angle = 45,
                                     hjust = 1))
  print(ggplotly(p1))
  
  p2 <- ggplot(data = tmp) +
    facet_wrap(~ Sex,
               nrow = 1) +
    geom_line(aes(x = Group,
                  y = lgt,
                  group = MouseID),
              size = 1,
              position = position_dodge(0.3)) + 
    geom_point(aes(x = Group,
                   y = lgt,
                   fill = MouseID),
               size = 3,
               alpha = 0.6,
               shape = 21,
               position = position_dodge(0.3)) + 
    scale_x_discrete("Diet/Week") + 
    scale_y_continuous("Logit of Relative Abundance") + 
    scale_fill_discrete("Mouse ID") +
    ggtitle(paste(tax,
                  over1pct[i],
                  sep = ": ")) +
    theme(plot.title = element_text(hjust = 0.5),
          axis.text.x = element_text(angle = 45,
                                     hjust = 1))
  print(ggplotly(p2))
  
  m1 <- lmerTest::lmer(lgt ~ Diet + Week + Sex + (1|MouseID),
                       # weights = 1/(Counts + 0.5),
                       data = tmp)
  print(summary(m1))
}
```

### 3. Family
```{r Family, warning=FALSE,echo=FALSE,message=FALSE,fig.width=10,fig.height=7}
tax <- "Family"
dt2 <- counts_ra_by_tax_rank(dt1, tax)

mu <- aggregate(dt2$RA,
                by = list(Tax = dt2$Tax,
                          Week = dt2$Week,
                          Diet = dt2$Diet),
                FUN = "mean")

lvls <- aggregate(dt2$RA,
                  by = list(Tax = dt2$Tax),
                  FUN = "mean")
lvls <- lvls$Tax[order(lvls$x,
                       decreasing = TRUE)]

dt2$Tax <- factor(dt2$Tax,
                  levels = lvls)

dt2 <- droplevels(dt2)
dt2[, lgt := log(1 + (RA/(1-RA)))]
# length(unique(dt2$Tax))
# 26 unique classes

dt2$Group <- paste("Week",
                   dt2$Week,
                   dt2$Diet)
# unique(dt2$grp)
dt2$Group <- factor(dt2$Group,
                    levels = c("Week 5 AIN93M Control",
                               "Week 9 AIN93M Control",
                               "Week 5 PEITC",
                               "Week 9 PEITC"))

# Boxplots for Classes with RA ~>1% (minus ----
over1pct <- levels(dt2$Tax)[1:17]

for (i in 1:length(over1pct)) {
  tmp <- droplevels(dt2[Tax == over1pct[i], ])
  
  p1 <- ggplot(data = tmp) +
    facet_wrap(~ Sex,
               nrow = 1) +
    geom_line(aes(x = Group,
                  y = RA,
                  group = MouseID),
              size = 1,
              position = position_dodge(0.3)) + 
    geom_point(aes(x = Group,
                   y = RA,
                   fill = MouseID),
               size = 3,
               alpha = 0.6,
               shape = 21,
               position = position_dodge(0.3)) + 
    scale_x_discrete("Diet/Week") + 
    scale_y_continuous("Relative Abundance") + 
    scale_fill_discrete("Mouse ID") +
    ggtitle(paste(tax,
                  over1pct[i],
                  sep = ": ")) +
    theme(plot.title = element_text(hjust = 0.5),
          axis.text.x = element_text(angle = 45,
                                     hjust = 1))
  print(ggplotly(p1))
  
  p2 <- ggplot(data = tmp) +
    facet_wrap(~ Sex,
               nrow = 1) +
    geom_line(aes(x = Group,
                  y = lgt,
                  group = MouseID),
              size = 1,
              position = position_dodge(0.3)) + 
    geom_point(aes(x = Group,
                   y = lgt,
                   fill = MouseID),
               size = 3,
               alpha = 0.6,
               shape = 21,
               position = position_dodge(0.3)) + 
    scale_x_discrete("Diet/Week") + 
    scale_y_continuous("Logit of Relative Abundance") + 
    scale_fill_discrete("Mouse ID") +
    ggtitle(paste(tax,
                  over1pct[i],
                  sep = ": ")) +
    theme(plot.title = element_text(hjust = 0.5),
          axis.text.x = element_text(angle = 45,
                                     hjust = 1))
  print(ggplotly(p2))
  
  m1 <- lmerTest::lmer(lgt ~ Diet + Week + Sex + (1|MouseID),
                       # weights = 1/(Counts + 0.5),
                       data = tmp)
  print(summary(m1))
}
```

### 4. Genus
```{r Genus, warning=FALSE,echo=FALSE,message=FALSE,fig.width=10,fig.height=7}
tax <- "Genus"
dt2 <- counts_ra_by_tax_rank(dt1, tax)

mu <- aggregate(dt2$RA,
                by = list(Tax = dt2$Tax,
                          Week = dt2$Week,
                          Diet = dt2$Diet),
                FUN = "mean")

lvls <- aggregate(dt2$RA,
                  by = list(Tax = dt2$Tax),
                  FUN = "mean")
lvls <- lvls$Tax[order(lvls$x,
                       decreasing = TRUE)]

dt2$Tax <- factor(dt2$Tax,
                  levels = lvls)

dt2 <- droplevels(dt2)
dt2[, lgt := log(1 + (RA/(1-RA)))]
# length(unique(dt2$Tax))
# 26 unique classes

dt2$Group <- paste("Week",
                   dt2$Week,
                   dt2$Diet)
# unique(dt2$grp)
dt2$Group <- factor(dt2$Group,
                    levels = c("Week 5 AIN93M Control",
                               "Week 9 AIN93M Control",
                               "Week 5 PEITC",
                               "Week 9 PEITC"))

# Boxplots for Classes with RA ~>1% (minus ----
over1pct <- levels(dt2$Tax)[1:20]

for (i in 1:length(over1pct)) {
  tmp <- droplevels(dt2[Tax == over1pct[i], ])
  
  p1 <- ggplot(data = tmp) +
    facet_wrap(~ Sex,
               nrow = 1) +
    geom_line(aes(x = Group,
                  y = RA,
                  group = MouseID),
              size = 1,
              position = position_dodge(0.3)) + 
    geom_point(aes(x = Group,
                   y = RA,
                   fill = MouseID),
               size = 3,
               alpha = 0.6,
               shape = 21,
               position = position_dodge(0.3)) + 
    scale_x_discrete("Diet/Week") + 
    scale_y_continuous("Relative Abundance") + 
    scale_fill_discrete("Mouse ID") +
    ggtitle(paste(tax,
                  over1pct[i],
                  sep = ": ")) +
    theme(plot.title = element_text(hjust = 0.5),
          axis.text.x = element_text(angle = 45,
                                     hjust = 1))
  print(ggplotly(p1))
  
  p2 <- ggplot(data = tmp) +
    facet_wrap(~ Sex,
               nrow = 1) +
    geom_line(aes(x = Group,
                  y = lgt,
                  group = MouseID),
              size = 1,
              position = position_dodge(0.3)) + 
    geom_point(aes(x = Group,
                   y = lgt,
                   fill = MouseID),
               size = 3,
               alpha = 0.6,
               shape = 21,
               position = position_dodge(0.3)) + 
    scale_x_discrete("Diet/Week") + 
    scale_y_continuous("Logit of Relative Abundance") + 
    scale_fill_discrete("Mouse ID") +
    ggtitle(paste(tax,
                  over1pct[i],
                  sep = ": ")) +
    theme(plot.title = element_text(hjust = 0.5),
          axis.text.x = element_text(angle = 45,
                                     hjust = 1))
  print(ggplotly(p2))
  
  m1 <- lmerTest::lmer(lgt ~ Diet + Week + Sex + (1|MouseID),
                       # weights = 1/(Counts + 0.5),
                       data = tmp)
  print(summary(m1))
}
```